The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Usually feature extraction is applied for dimension reduction in hyperspectral data classification problems. Some studies show that nonparametric weighted feature extraction (NWFE; Kuo and Landgrebe, 2004) is a powerful tool to extract hyperspectral image features for classification. Recently, some studies also show that kernel-based methods are computationally efficient, robust and stable for pattern...
There is a need to identify and extract the most useful information from spectral and temporal features, where usefulness is measured in terms of signal classification or target detection. For this reason, instead of using the entire spectral and temporal feature space, pertinent features are extracted to reduce dimensionality. The classification accuracy increases if the distributions of the classes...
After reviewing and discussing the difficulties of dealing with automatic interpretation methods in SAR imagery, the advantages of using a multiscale time-frequency framework will be established. Then, a specific technique for automatic spot detection, based on the Wavelet Transform (WT), will be presented and justified. The performance of the proposed algorithm will be tested, validated and compared...
The accuracy of supervised land cover classifications depends on variables like the chosen algorithm, adequate training data and the selection of features. It has been shown that classification results can be improved by classifier ensembles. In the present study decision trees have been generated with random selections of all available features and combined into such a multiple classifier. The influence...
In ISAR systems, fully polarimetric capabilities have not been fully exploited for target classification or recognition. In this paper, a full system that reconstructs the polarimetric ISAR image and classifies the target is proposed and tested on simulated data.
The first testbed of X-band radar systems deployed by the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA), in central Oklahoma called IP-1 (Integrated Project 1) will have a low unambiguous velocity due to their short wavelength, and increasing the PRF will result in multiple trip overlays since storms can extend over a large distance. The range-velocity ambiguity is more severe...
Reflectance pattern and spatial pattern characterize the geospatial data. Current semantic-enabled framework retrieval system extract primitive features based on color, texture (Spatial Gray Level Dependency - SGLD matrices), and shape from the segmented homogenous region. This system can use only three bands (true color or false color) at a time to capture color information as it converts RGB space...
In this paper, a new discrimination scheme is proposed for classifying multi-group hyperspectral image. The smooth localized complex exponentials (SLEX) library and a modified Bottom-Up Generalized Local Discriminant Bases (MGLDB-BU) algorithm are adopted for extracting ideal features for discrimination. With the extracted features, a mechanism based on Chernoff information is employed for classification...
This paper presents a fuzzy logic fusion methodology for land-cover classification with multi-temporal/polarization Radarsat-1 and ENVISAT ASAR data. For feature extraction from each multi-temporal/polarization data, a traditional feature extraction approach (i.e. extraction of average backscattering coefficient, temporal variability and long-term coherence) and principal component analysis (PCA)...
Feature extraction is often applied for dimensionality reduction in hyperspectral data classification problems to mitigate the Hughes phenomenon. Some studies had proven that nonparametric weighted feature extraction (NWFE) is a powerful tool to extract well-described features for classification. NWFE concentrates only on the separability of spectral data, however, in many remotely sensed images,...
In this paper, we propose a new scheme to extrapolate wavelet features with respect to the resolution. By explicitly taking into account the acquisition process of satellite images, we compute how wavelet features behave when the resolution changes. This approach is validated by classifying satellite images with different resolutions.
Many features of interest in remote sensing imagery, such as roads, rivers, clouds, trees, and buildings can have high spectral, structural, and textural variability due to variations in reflectance, resolution, intrinsic shape, etc. Nevertheless they have distinctive qualitative properties of their own from the point of human perception. For instance, clouds are typically fluffy or wispy, roads have...
A phenomenon is defined as any state or process known through the senses rather than by intuition or reasoning, and thus is an observable event, especially something special or unusual. A geophysical phenomenon in the context of geoscience data can be characterized as a spatial region which is significantly different from the rest of the image; having higher/lower than average background intensity...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.